BACKGROUND Myriad manifestations of cardiovascular involvement have been described in patients with coronavirus disease 2019 (COVID-19), but there have been no reports of COVID-19 affecting the cardiac conduction system. The PR interval on the electrocardiogram (ECG) normally shortens with increasing heart rate (HR). The case of a patient with COVID-19 manifesting Mobitz type 1 atrioventricular (AV) block that normalized as the patient's condition improved prompted us to investigate PR interval behavior in patients with COVID-19.OBJECTIVE The purpose of this study was to characterize PR interval behavior in hospitalized patients with COVID-19 and to correlate that behavior with clinical outcomes.METHODS This study was a cross-sectional cohort analysis of confirmed COVID-19 cases (March 26, 2020, to April 25, 2020. We reviewed pre-COVID-19 and COVID-19 ECGs to characterize AV conduction by calculating the PR interval to HR (PR:HR) slope. Clinical endpoints were death or need for endotracheal intubation.RESULTS ECGs from 75 patients (246 pre-COVID-19 ECGs and 246 COVID-19 ECGs) were analyzed for PR:HR slope. Of these patients, 38 (50.7%) showed the expected PR interval shortening with increasing HR (negative PR:HR slope), whereas 37 (49.3%) showed either no change (8 with PR:HR slope 5 0) or paradoxical PR interval prolongation (29 with positive PR:HR slope) with increasing HR. Patients without PR interval shortening were more likely to die (11/37 [29.7%] vs 3/38 [7.9%]; P 5 .019) or require endotracheal intubation (16/37 [43.2%] vs 8/38 [21.1%]; P 5 .05) compared to patients with PR interval shortening.CONCLUSION Half of patients with COVID-19 showed abnormal PR interval behavior (paradoxical prolongation or lack of shortening) with increasing HR. This finding was associated with increased risk of death and need for endotracheal intubation.

Hospital discharge is a high-risk time period, and acute myocardial infarction (AMI) patients often have early readmissions. The authors hypothesized that a multifaceted AMI care coordination program would reduce early hospital readmission rates. The outcomes of patients receiving care coordination (n = 304) were compared to patients receiving standard care (n = 192). Multivariable analyses of the outcomes were conducted by conditional logistic regression of propensity score matched sets. The primary outcome-hospital readmission within 30 days of discharge-occurred in 18% of standard care patients and 11.8% of care coordination patients. Patients receiving care coordination demonstrated a 48% reduction in odds of readmission within 30 days (odds ratio = 0.52; P = .04; 95% CI = 0.28-0.97). These results are the first to demonstrate that inclusion in an AMI-specific care coordination program is associated with a significantly lower risk of 30-day hospital readmission.

Problem Definition: Defibrillation within 2 minutes after ventricular fibrillation (VFib) and ventricular tachycardia (VTach) cardiac arrest has improved survival to discharge and five-year survival rates. The goal of this study was to identify how often patients were defibrillated within this recommended 2-minute interval at a single institution. A retrospective chart review of the code blue database over a 21-month time period revealed 24 VFib/VTach cardiac arrests. Time to defibrillation for each event, defined as time of identification of VFib/VTach arrest to time of delivery of the first defibrillation, was calculated. Approximately 67% (22/34) of patients who experienced VFib/VTach arrest were not defibrillated within 2 minutes and 8% (3/34) did not receive defibrillation at all. The data was further stratified based on event location (ICU versus non-ICU) and compared using chi-squared analysis, with statistical significance defined as p<0.05. A significantly higher number of delayed defibrillations occurred in the non-ICU cohort compared to the ICU cohort (11/34 versus 3/34, p=0.0028). Intervention: We utilized code blue simulation sessions and an educational module to train nursing staff, who are often first at bedside, to promptly defibrillate VFib/VTach. Methods: 36 nurses out of 53 ACLS certified nurses were recruited from a single nursing unit. Groups of 2 or 3 nurses completed code blue simulation sessions to establish a baseline time to defibrillation. They were then given 2 weeks to complete an assigned educational module. Upon completion, they will be brought in for a second round of simulation sessions to assess whether their time to defibrillation has improved. Results: Out of the 15 simulation sessions that were done in the first round, 33% (5/15) ended with delayed defibrillation and 27% (4/15) ended with no defibrillation. The simulation data correlated with the retrospective chart review data. Next Steps: The second round of simulation sessions will take place in two weeks. Post-intervention data will be collected and analyzed to determine if the nursing educational module was effective. If it is, we hope to make the simulation sessions and educational module a hospital-wide initiative to improve time to defibrillation.

The goal of this study was to identify how often 2 independent centers defibrillated patients within the American Heart Association recommended 2-minute time interval following ventricular fibrillation/ventricular tachycardia arrest. A retrospective chart review revealed significant delays in defibrillation. Simulation sessions and modules were implemented to train nursing staff in a single nursing unit at a Philadelphia teaching hospital. Recruited nurses completed a code blue simulation session to establish a baseline time to defibrillation. They were then given 2 weeks to complete an online educational module. Upon completion, they participated in a second set of simulation sessions to assess improvement. First round simulations resulted in 33% with delayed defibrillation and 27% no defibrillation. Following the module, 77% of the second round of simulations ended in timely defibrillation, a statistically significant improvement (P < 0.00001). Next steps involve prospective collection of the code blue data to analyze improvement in real code blue events.